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Int J Clin Pharmacol Toxicol. 2017;6(1):242-249. Epub 2017 Jan 03.

CYP2B6 Genotype Guided Dosing of Propofol Anesthesia in the Elderly based on Nonparametric Population Pharmacokinetic Modeling and Simulations.

International journal of clinical pharmacology & toxicology

Andy R Eugene


  1. Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental, Therapeutics, Gonda 19, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.

PMID: 28154789 PMCID: PMC5282793


OBJECTIVE: The primary aim of this article is to test the hypothesis that nonparametric pharmacometric modeling will accurately identify CYP2B6 genotype subgroups based on data from a study that reported results based on parametric pharmacokinetics (PK).

METHODS: Propofol concentration-time data were originally reported in the Kansaku et al. 2011 publication. Nonparametric Nonlinear Mixed Effects Modeling (NLME) was conducted using the PMETRICS R package while population pharmacokinetic model parameters were estimated using a FORTRAN compiler. Finally, model-based dosing simulations were conducted in the MATLAB Simbiology.

RESULTS: A total of 51 patients were included in the final PK analysis. A two-compartment gamma multiplicative error model adequately described the propofol concentration-time data. The precision of the goodness-of-fit plots resulted in an R

CONCLUSION: Based on the pharmacometric modeling and simulation, if no dosage adjustments are made for the elderly CYP2B6 AA and AG genotypes, a 250% higher propofol blood exposure will be evident within 1-hour from the start of the infusion. Thus, based on the pharmacokinetic model, genotyping elderly patients for the CYP2B6 AA and AG gene variants will decrease the total propofol blood exposure during anesthesia and sedation when an infusion dose adjustment is made to 25mg/kg/min.

Keywords: anesthesia; genotype; nonparametric pharmacokinetics; precision medicine; propofol

Conflict of interest statement

The author declares no conflict of interests.


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